{"title":"命题证明系统中复杂性度量和大小-空间权衡的空间表征","authors":"Theodoros Papamakarios , Alexander Razborov","doi":"10.1016/j.jcss.2023.04.006","DOIUrl":null,"url":null,"abstract":"<div><p>We identify two new clusters of proof complexity measures equal up to polynomial and <span><math><mi>log</mi><mo></mo><mi>n</mi></math></span> factors. The first cluster contains the logarithm of tree-like resolution size, regularized clause and monomial space, and clause space, ordinary and regularized, in regular and tree-like resolution. Consequently, separating clause or monomial space from the logarithm of tree-like resolution size is equivalent to showing strong trade-offs between clause space and length, and equivalent to showing super-critical trade-offs between clause space and depth. The second cluster contains width, <span><math><msub><mrow><mi>Σ</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> space (a generalization of clause space to depth 2 Frege systems), ordinary and regularized, and the logarithm of tree-like <span><math><mi>R</mi><mo>(</mo><mi>log</mi><mo></mo><mo>)</mo></math></span> size. As an application, we improve a known size-space trade-off for polynomial calculus with resolution. We further show a quadratic lower bound on tree-like resolution size for formulas refutable in clause space 4, and introduce a measure intermediate between depth and the logarithm of tree-like resolution size.</p></div>","PeriodicalId":50224,"journal":{"name":"Journal of Computer and System Sciences","volume":"137 ","pages":"Pages 20-36"},"PeriodicalIF":1.1000,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Space characterizations of complexity measures and size-space trade-offs in propositional proof systems\",\"authors\":\"Theodoros Papamakarios , Alexander Razborov\",\"doi\":\"10.1016/j.jcss.2023.04.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We identify two new clusters of proof complexity measures equal up to polynomial and <span><math><mi>log</mi><mo></mo><mi>n</mi></math></span> factors. The first cluster contains the logarithm of tree-like resolution size, regularized clause and monomial space, and clause space, ordinary and regularized, in regular and tree-like resolution. Consequently, separating clause or monomial space from the logarithm of tree-like resolution size is equivalent to showing strong trade-offs between clause space and length, and equivalent to showing super-critical trade-offs between clause space and depth. The second cluster contains width, <span><math><msub><mrow><mi>Σ</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> space (a generalization of clause space to depth 2 Frege systems), ordinary and regularized, and the logarithm of tree-like <span><math><mi>R</mi><mo>(</mo><mi>log</mi><mo></mo><mo>)</mo></math></span> size. As an application, we improve a known size-space trade-off for polynomial calculus with resolution. We further show a quadratic lower bound on tree-like resolution size for formulas refutable in clause space 4, and introduce a measure intermediate between depth and the logarithm of tree-like resolution size.</p></div>\",\"PeriodicalId\":50224,\"journal\":{\"name\":\"Journal of Computer and System Sciences\",\"volume\":\"137 \",\"pages\":\"Pages 20-36\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-05-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computer and System Sciences\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0022000023000478\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer and System Sciences","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022000023000478","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Space characterizations of complexity measures and size-space trade-offs in propositional proof systems
We identify two new clusters of proof complexity measures equal up to polynomial and factors. The first cluster contains the logarithm of tree-like resolution size, regularized clause and monomial space, and clause space, ordinary and regularized, in regular and tree-like resolution. Consequently, separating clause or monomial space from the logarithm of tree-like resolution size is equivalent to showing strong trade-offs between clause space and length, and equivalent to showing super-critical trade-offs between clause space and depth. The second cluster contains width, space (a generalization of clause space to depth 2 Frege systems), ordinary and regularized, and the logarithm of tree-like size. As an application, we improve a known size-space trade-off for polynomial calculus with resolution. We further show a quadratic lower bound on tree-like resolution size for formulas refutable in clause space 4, and introduce a measure intermediate between depth and the logarithm of tree-like resolution size.
期刊介绍:
The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions.
Research areas include traditional subjects such as:
• Theory of algorithms and computability
• Formal languages
• Automata theory
Contemporary subjects such as:
• Complexity theory
• Algorithmic Complexity
• Parallel & distributed computing
• Computer networks
• Neural networks
• Computational learning theory
• Database theory & practice
• Computer modeling of complex systems
• Security and Privacy.